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Collections including paper arxiv:2211.03831

AugmentedLearning

What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning

Paper • 2312.15685 • Published Dec 25, 2023 • 17
mistralai/Mixtral-8x7B-Instruct-v0.1

Text Generation • Updated Aug 19 • 877k • • 4.18k
microsoft/phi-2

Text Generation • Updated Apr 29 • 263k • 3.24k
TinyLlama/TinyLlama-1.1B-Chat-v1.0

Text Generation • Updated Mar 17 • 1.15M • 1.09k

MOE papers to read

Copied from MoE using https://huggingface.co/spaces/librarian-bots/collection_cloner.

QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models

Paper • 2310.16795 • Published Oct 25, 2023 • 26
Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference

Paper • 2308.12066 • Published Aug 23, 2023 • 4
Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference

Paper • 2303.06182 • Published Mar 10, 2023 • 1
EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

Paper • 2112.14397 • Published Dec 29, 2021 • 1

Papers: MoE/Ensemble

Papers related to Mixture of Experts topics.

QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models

Paper • 2310.16795 • Published Oct 25, 2023 • 26
Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 4
The Consensus Game: Language Model Generation via Equilibrium Search

Paper • 2310.09139 • Published Oct 13, 2023 • 12
Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning

Paper • 2310.03094 • Published Oct 4, 2023 • 12

Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time

Paper • 2310.17157 • Published Oct 26, 2023 • 11
Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers

Paper • 2305.15805 • Published May 25, 2023 • 1
Compress, Then Prompt: Improving Accuracy-Efficiency Trade-off of LLM Inference with Transferable Prompt

Paper • 2305.11186 • Published May 17, 2023 • 1
Composable Sparse Fine-Tuning for Cross-Lingual Transfer

Paper • 2110.07560 • Published Oct 14, 2021 • 1

QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models

Paper • 2310.16795 • Published Oct 25, 2023 • 26
Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference

Paper • 2308.12066 • Published Aug 23, 2023 • 4
Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference

Paper • 2303.06182 • Published Mar 10, 2023 • 1
EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

Paper • 2112.14397 • Published Dec 29, 2021 • 1

LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Paper • 2310.08659 • Published Oct 12, 2023 • 22
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 44
ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers

Paper • 2309.16119 • Published Sep 28, 2023 • 1
LoRA ensembles for large language model fine-tuning

Paper • 2310.00035 • Published Sep 29, 2023 • 2

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